Monologue Details Production Fine-Tuning Playbook

The key lesson is that production fine-tuning starts with disciplined measurement, not model training. Monologue’s workflow shows how a narrow, high-volume task can justify owning the model layer.

• –An evaluation harness exposed failure patterns before optimization began.
• –DSPy and GEPA improved prompts and accuracy before fine-tuning was attempted.
• –Synthetic examples derived from evaluation failures created targeted training data.
• –Reported latency fell from 1,043ms to 223ms at P50 and from 9,593ms to 2,200ms at P99.
• –The approach turns dictation quality and responsiveness into a product moat, but requires continuous data, evaluation, and deployment work.